---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- generated_from_trainer
model-index:
- name: sft-zephyr-7b-beta-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# sft-zephyr-7b-beta-v1

This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4927

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0538        | 0.19  | 50   | 1.1364          |
| 0.7744        | 0.37  | 100  | 0.7777          |
| 0.5936        | 0.56  | 150  | 0.6507          |
| 0.5449        | 0.74  | 200  | 0.6087          |
| 0.501         | 0.93  | 250  | 0.5840          |
| 0.5752        | 1.12  | 300  | 0.5552          |
| 0.4542        | 1.3   | 350  | 0.5419          |
| 0.5115        | 1.49  | 400  | 0.5243          |
| 0.4224        | 1.67  | 450  | 0.5188          |
| 0.4486        | 1.86  | 500  | 0.5055          |
| 0.3865        | 2.04  | 550  | 0.5038          |
| 0.4193        | 2.23  | 600  | 0.5048          |
| 0.4294        | 2.42  | 650  | 0.4995          |
| 0.4077        | 2.6   | 700  | 0.5014          |
| 0.4667        | 2.79  | 750  | 0.4985          |
| 0.4226        | 2.97  | 800  | 0.4937          |
| 0.4195        | 3.16  | 850  | 0.4920          |
| 0.338         | 3.35  | 900  | 0.4923          |
| 0.3943        | 3.53  | 950  | 0.4926          |
| 0.3953        | 3.72  | 1000 | 0.4927          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.15.0